As reported by the U.S. Center for Disease Control (CDC), there are over 100,000 bacteria-related deaths per year in the United States alone. Of these infections, large percentages are caused by antibiotic-resistant microorganisms. Infections due to resistant organisms are occurring at higher frequencies and this increase in resistance is only worsened by the slowing pace of development of new antibiotic agents. Indeed, there has been a 53% decrease in FDA approved antibiotic agents between the years 1983 and 2002 (Spellberg, B, J H Powers, E P Brass, L G Miller, and J E Edwards, Jr., Trends in antimicrobial drug development: implications for the future, Clin. Infect. Dis. 38, 1279-1286, May 2004). With the number of available antibiotics decreasing, there is an ever increasing need to determine the most appropriate antibiotic therapy. In an attempt to preserve the effectiveness of available antibiotics, stewardship programs have also been implemented and their effectiveness studied (MacDougall, C. and R. E. Polk, Antimicrobial Stewardship Programs in Health Care Systems, Clinical Microbiology Reviews 18, 638-656, October 2005). Nonetheless, the compounded problem of emerging resistance and slowing development of new antibiotics has left many clinicians frustrated (Talbot, G H, J Bradley, J E Edwards, Jr., D Gilbert, M Scheld, and J G Bartlett, Bad Bugs Need Drugs: An Update on the Development Pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America Clinical Infectious Diseases 42, 657-668, March 2006). While development of new antibiotics is one approach, it only addresses part of the problem. What it does not address is the need and role that rapid diagnostics have in appropriately managing antibiotics. In some cases, overexposure of bacteria can ultimately lead to pan-resistant organisms for which there are no currently available antibiotics that can be used for effective treatment (Boucher, H W, G H Talbot, J S Bradley, J E Edwards, Jr, D Gilbert, L B Rice, M Scheld, B Spellberg, and J Bartlett, Bad Bugs, No Drugs: No ESKAPE! An Update from the Infectious Diseases Society of America, Clin. Infect Dis 48, 1-12, January 2009). Even organisms that are not pan-resistant can be extremely harmful to patient populations and create a severe burden on the health system (Chu V H, Crosslin D R, Friedman J Y, et al., Staphylococcus aureus bacteremia in patients with prosthetic devices: costs and outcomes, Am J Med 118, 1416, December 2005). One such organism is methicillin-resistant Staphylococcus aureus (MRSA). MRSA-related infections can appear in many different forms, such as blood infections, skin infections, respiratory infections and others (Boucher H W, G R Corey, Epidemiology of methicillin-resistant Staphylococcus aureus, Clin. Infect Dis. 46, S344-9, June 2008). In the US, there are an estimated 19,000 MRSA-related deaths per year, which leads to more deaths in the US than HIV/AIDS and Tuberculosis combined (Klevens R M, J R Edwards, F C Tenover, L C McDonald, T Horan, R Gaynes, Changes in the epidemiology of methicillin-resistant Staphylococcus aureus in intensive care units in US hospitals, 1992-2003, Clin. Infect Dis 42, 389-91, February 2006; and Boucher H W, G R Corey, Epidemiology of methicillin-resistant Staphylococcus aureus, Clin. Infect Dis. 46, S344-9, June 2008). The number of MRSA cases per year has historically been rapidly increasing—in 2003, there were a reported 400,000 inpatient MRSA-related cases (Noskin G A, R J Rubin, J J Schentag et al., National trends in Staphylococcus aureus infection rates: impact on economic burden and mortality over a 6-year period (1998-2003), Clin. Infect Dis 45, 1132-40, November 2007). MRSA is now so common that in intensive care units (ICU) it accounts for more than 60% of S. aureus isolates (National Nosocomial Infections Surveillance (NNIS) System report, data summary from January 1992 through June 2004, issued October 2004, Am. J. Infect Control 32, 470-85, October 2004).
One method that has been commercialized to rapidly identify MRSA infections is molecular diagnostics. Identification of resistant microorganisms by the use of molecular diagnostics has shown tremendous progress and usefulness. In the case of MRSA, molecular tests are based on detection of the mecA gene in addition to a sequence that is specific to S. aureus. While molecular diagnostics provide rapid information that is useful for screening and even initial choice of antibiotic, it does not necessarily determine the ideal antibiotic, based on the minimum inhibitory concentration that ultimately determines the most appropriate antibiotic therapy. This key fact is true for many detection methods including impedance (Yang, L., Y. Li and G. F. Erf, Interdigitated array microelectrode-based electrochemical impedance immunosensor for detection of Escherichia coli O157:H7, Anal. Chem. 76, 1107-1113, 2004), quartz crystal microbalance (Su, X.-L. and Y. Li, A self-assembled monolayer-based piezoelectric immunosensor for rapid detection of Escherichia coli O157:H7, Biosens, Bioelectron. 19, 563-574, January 2004), bioluminescence (Fujinami, Y., M. Kataoka, K. Matsushita, H. Sekiguchi, T. Itoi, K. Tsuge and Y. Seto, Sensitive detection of bacteria and spores using a portable bioluminescence ATP measurement assay system distinguishing from white powder materials, J. Health Sci. 50, 126-132, 2004), plasmon resonance (Fratamico, P. M., T. P. Strobaugh, M. B. Medina and A. G. Gehring, Detection of Escherichia coli O157:H7 using a surface plasmon resonance biosensor, Biotechnol. Tech. 12, 571-576, July 1998), microcantilever sensors (Ilic, B., D. Czaplewski, H. G. Craighead, P. Neuzil, C. Campagnolo and C. Batt, Mechanical resonant immunospecific biological detector, Appl. Phys. Lett. 77, 450-452, 2000), among others.
In order to determine the most appropriate antibiotic therapy, antibiotic susceptibility testing must be performed, where the minimum inhibitory concentration (MIC) is measured. The MIC information gleaned from MIC values can have a major impact on patient mortality. For example, in one study, mortality rates related to ventilator-associated pneumonia were reduced from 60.8% to 33.3% when antibiotics were initially properly administered (Kumar A, D Roberts D, Wood K E, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock, Crit. Care Med 2006; 34:1589-96, 2006). To achieve optimum treatment, antibiotic susceptibility testing and reported MIC values must be performed. This is even the case when a rapid diagnostic has been used to determine resistance based on the mecA gene. For example, when the MIC value of a MRSA isolate is near or above 2 μg/mL, a therapeutic agent other than vancomycin (e.g. daptomycin or linezolid) should be implemented (Deresinski, S., Counterpoint: Vancomycin and Staphylococcus aureus—an antibiotic enters obsolescence. Clin. Infect Dis. 44, 1543, 2007; and Sakoulas, G, Moise-Broder, P A, Schentag, J, et al., Relationship of MIC and Bactericidal Activity to Efficacy of Vancomycin for Treatment of Methicillin-Resistant Staphylococcus aureus Bacteremia, J. Clin. Microbiol 42, 2398, 2004).
The emergence and spread of antibiotic resistance is a global health concern, as pathogenic species increasingly adapt to antimicrobial agents and classes. Standard antimicrobial susceptibility testing (AST) protocols typically take over 24 hours for a full analysis; as a result, patients are often prescribed empiric therapies prior to diagnosis. Incorrect empiric therapies, such as the inadequate, inappropriate, or overly broad-spectrum use of antimicrobial agents, result in poor patient response and contribute to the increase in multi-drug resistant pathogens. Decreasing the use of unnecessary antibiotics and treating patients with narrow-spectrum agents will help confront this global problem; one approach towards this goal is through the development of rapid AST for earlier diagnosis. Earlier diagnosis will enable more appropriate therapies to be prescribed, reduce antibiotic use, and may lead to more effective treatments. Subsequently, it will reduce health care costs, length of hospital stays, and the spread of antimicrobial resistance.
Traditional methods of microbial identification and differentiation of the infectious organisms rely on phenotypic characteristics, such as morphology and growth. However, molecular diagnostic techniques are increasingly used as adjuncts in clinical AST. These diagnostic techniques, in particular the polymerase chain reaction (PCR), enable rapid detection of pathogen-derived nucleic acids in clinical specimens, thereby reducing identification and diagnosis to a few hours. However, molecular methods are typically more expensive than phenotype-based assays, genetically identical bacteria may exhibit phenotypic heterogeneity potentially leading to inappropriate treatments, and only a few resistance genes have been firmly associated with phenotypic resistance. Ultimately, phenotype-based methods, specifically determining the minimum inhibitory concentration (MIC) of the bacterial species, remains the ‘gold standard’ for AST. Currently, rapid clinical AST measurement tools utilize the growth-based microdilution technique (incorporated by the various commercially available AST systems) to determine the MIC, which is defined as the lowest antibiotic concentration that inhibits visible growth after overnight incubation. Nevertheless, the complete AST protocol, from pathogen isolation to MIC determination, takes well over 24 hours due to the combination of long culture time (18-24 hours) and the AST measurement time (requiring 6-24 hours). Towards the goal of achieving faster AST measurements, there is a need for the improvement of optical detection methods and/or the development of new approaches to detect bacterial proliferation.
Microfluidic technologies have been used to reduce the turnaround time for AST. By confining single or small cell populations of bacteria in nanoliter volume droplets, the effective concentration of cells in a system increases. Furthermore, the droplet systems are not subjected to dilution effects that are apparent in bulk systems; as a result, cellular biochemical signals or reaction products accumulate in the droplet more rapidly. Using a microfluidic droplet system, the MIC values for Staphylococcus aureus cells that were exposed to antibiotics were obtained within 7 hours by measuring the accumulation of a fluorescence viability indicator. Another microfluidic approach confines cells in gas-permeable microchannels with high surface-to-volume ratios, which increases oxygen diffusion into the system. Increased levels of oxygen available to the cells resulted in faster replication rates and bacterial cells accumulated in the channels more rapidly. Escherichia coli (E. coli) bacteria exposed to antibiotics were cultivated in these high surface-to-volume microfluidic channels, allowing AST measurements based on the turbidity of the sample to be obtained within 2 hours from the start of cultivation.
There is also a need for detection of bacterial/microbial contamination of food, including particularly agricultural food testing. Accurate methods for detecting and identifying diverse groups of pathogenic bacteria are essential for protecting the public from foodborne bacteria.
Recently, asynchronous magnetic bead rotation (AMBR) has been applied towards bio-sensing applications, such as bacterial cell and analyte detection. See, e.g., U.S. Publication No. 2008/0220411 to McNaughton et al. The AMBR biosensors are based on a technique in which a magnetic bead is placed within an external rotating magnetic field and changes in this magnetic bead's physical properties (i.e. shape and volume), or changes in its environment, translate into detectable changes in the bead's rotation rate. For instance, when a viable cell that is attached to a magnetic bead grows, the rotation rate of an asynchronously rotating magnetic bead may decrease. However, under bulk experimental conditions, AMBR biosensors can be subjected to bead translation, magnetic interactions (if the sample is not sufficiently dilute), surface adhesion and stiction effects, which may reduce the efficiency or accuracy of the system. Further, although it is desirable to optically monitor the rotation rate of the magnetic bead(s); although larger beads may be more readily visualized, it would be helpful to enhance the visualization of even small magnetic particles used as probes.
Thus, there is a need for AMBR-based systems that allow for determination of bacterial growth and binding in a manner that avoids many of the issues discussed above. In addition, it would be beneficial to allow parallel testing of a plurality of rotating magnetic bead assays. Other improvements to the existing AMBR systems may address the design of the sensing apparatus, including the camera or visualization system, controlling the formation of aggregates of magnetic beads for monitoring cell growth, sorting of magnetic particles prior or during AMBR (e.g., to separate those with bound cells from those that are unbound), preparation of coated beads having appropriate buoyancy, detection of cell growth even when the system is not rotating the magnetic beads, detection of bacteria in a blood sample directly, enhancing or speeding-up bacterial growth in combination with AMBR, and droplet-based microfluidic platforms that use AMBR biosensors for rapid growth studies at the single cell and small cell-population level.
The variations of the AMBR biosensors, systems and methods described herein may be used in any combination or sub-combination. At the single cell level, heterogeneity studies or single cell kinetics studies become possible due to the high sensitivity of these improved systems. For clinical AST, studies of collective cellular behavior are desired since cells act in a cooperative manner to provide protection, improve survival against competitors and initiate quorum sensing. Towards this end, the AMBR systems described herein may allow rapid measurement of changes in cell growth in response to external factors, and offer improvements over currently existing biosensors, including previously described AMBR sensors.